Generative AI and Foreign Language Learning From a Cognitive Linguistics Perspective
近年、生成AIおよびそれを用いたLLM（大規模言語モデル）の発展により外国語学習の意義についての議論が活発になっている(大木他, 2025； 李・青山, 2025; 隅田, 2022； 瀧田・西島, 2019）。そこで、本論考では、認知言語学とLLMとの関係性およびそこから得られる帰結としての今後の外国語学習の方向性について考察を行う。結論として、外国語学習には、その言語共同体に固有の慣習的な世界の捉え方を学ぶという教養的側面があり、したがって、今後どれほどAIによる通訳機能が発達したとしても、外国語学習の意義が完全に失われることはないと主張することになる。本論考では、日本で大多数を占める単一言語話者 (monolinguals) を想定して主に議論を進めるが、本論考の主張に従うならば、単一言語話者こそ外国語を学習する意義が大きいということになる。
Recent advances in generative artificial intelligence, particularly large language models (LLMs) and neural machine translation, have prompted renewed debate about the significance of foreign language learning. As AI-mediated communication increasingly enables speakers to interact across languages without directly acquiring those languages themselves, some have questioned whether foreign language education will remain necessary. This paper reconsiders this issue from the perspective of Cognitive Linguistics and argues that foreign language learning retains an essential intellectual and cultural value that cannot be outsourced to AI technologies. First, the paper explores theoretical affinities between Cognitive Linguistics and contemporary LLMs. Usage-based approaches in Cognitive Linguistics conceptualize linguistic knowledge as a structured network emerging from repeated exposure to vast numbers of usage events. Similarly, LLMs simulate linguistic competence through large-scale statistical learning over massive corpora. Moreover, recent developments in predictive coding models in neuroscience suggest that human cognition itself may operate through probabilistic prediction and error minimization, lending further plausibility to parallels between human language processing and generative models. From a constructive research perspective, therefore, LLMs can be viewed not merely as engineering tools but as experimental hypotheses about how linguistic knowledge may be organized and processed. Second, drawing on the notion of construal and the “Thinking for Speaking” framework, the paper argues that languages differ not only in form but also in how they habitually direct speakers’ attention to particular aspects of experience. Each language encodes culturally and historically sedimented patterns of categorization, profiling, and perspective taking. Acquiring a language thus entails learning a community-specific way of attending to and conceptualizing the world. In this sense, language learning is inseparable from learning alternative cognitive styles. Usage-based semantics further suggests that such patterns are internalized through accumulated exposure to authentic linguistic instances, embedding collective cultural knowledge within the learner’s cognitive system. Third, the paper examines the impact of AI translation through the lenses of economic rationality, psychological adaptation to technology, and the outsourcing of cognitive functions. While communicative functions of language may increasingly be delegated to AI devices—much like memory has been partially outsourced to smartphones—this outsourcing risks reducing language to a mere instrumental tool. If language learning is evaluated solely in terms of communicative efficiency, AI solutions may appear sufficient. However, such a view overlooks the formative role of language in shaping thought and perception. The central claim advanced here is that foreign language learning possesses an irreducible educational function: it enables learners to recognize that their native way of construing the world is not universal and to develop a meta-cognitive, pluralistic perspective. This cultivation of multiple “ways of thinking for speaking” fosters intellectual flexibility and intercultural understanding—capacities that cannot be replicated by external translation technologies. Consequently, even in an era of highly sophisticated AI interpretation, the significance of foreign language learning will not disappear but should be reconceptualized beyond communication toward cognitive and humanistic development.
キーワード: 認知言語学; 大規模言語モデル; 使用基盤主義; 捉え方; 話すための思考; 教養的意義
Keywords: cognitive linguistics; construal; educational value; large language models (LLMs), usage-based approach; thinking for speaking
